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Heather Reese, A Danielle Iuliano, Neha N Patel, Shikha Garg, Lindsay Kim, Benjamin J Silk, Aron J Hall, Alicia Fry, Carrie Reed, Estimated Incidence of Coronavirus Disease 2019 (COVID-19) Illness and Hospitalization—United States, February–September 2020, Clinical Infectious Diseases, Volume 72, Issue 12, 15 June 2021, Pages e1010–e1017, https://doi.org/10.1093/cid/ciaa1780
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Abstract
In the United States, laboratory-confirmed coronavirus disease 2019 (COVID-19) is nationally notifiable. However, reported case counts are recognized to be less than the true number of cases because detection and reporting are incomplete and can vary by disease severity, geography, and over time.
To estimate the cumulative incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, symptomatic illnesses, and hospitalizations, we adapted a simple probabilistic multiplier model. Laboratory-confirmed case counts that were reported nationally were adjusted for sources of underdetection based on testing practices in inpatient and outpatient settings and assay sensitivity.
We estimated that through the end of September, 1 of every 2.5 (95% uncertainty interval [UI]: 2.0–3.1) hospitalized infections and 1 of every 7.1 (95% UI: 5.8–9.0) nonhospitalized illnesses may have been nationally reported. Applying these multipliers to reported SARS-CoV-2 cases along with data on the prevalence of asymptomatic infection from published systematic reviews, we estimate that 2.4 million hospitalizations, 44.8 million symptomatic illnesses, and 52.9 million total infections may have occurred in the US population from 27 February–30 September 2020.
These preliminary estimates help demonstrate the societal and healthcare burdens of the COVID-19 pandemic and can help inform resource allocation and mitigation planning.
(See the Major Article by Basavaraju et al on pages e1004–9 and the Editorial Commentary by Rosenberg and Bradley on pages e1018–20).
In the United States, the earliest known patients with coronavirus disease 2019 (COVID-19), the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, were associated with travel to affected countries or known contact with other infected persons [1]. By February 2020, persons with SARS-CoV-2 infection in the United States and no known exposure were detected [2]. Between 27 February and 30 September 2020, nearly 6.9 million laboratory-confirmed cases of domestically acquired infections were detected and reported nationally.
Persons with laboratory-confirmed SARS-CoV-2 infection reported through national surveillance do not represent all infected persons in the United States. Seroprevalence studies have shown a higher level of SARS-CoV-2 infection than has been reflected by confirmed case counts [3–7]. Most unreported infections were asymptomatic or mildly ill people who recovered without seeking medical care or testing [8–10]. However, even persons with SARS-CoV-2 infection in medical settings may not be tested or nationally reported as confirmed cases. Limited availability of tests, reagents, and laboratory capacity reduced case detection; in addition, patients may have avoided medical care settings or presented with nonspecific symptoms and not been suspected to have SARS-CoV-2 infection. Furthermore, not all infected persons will test positive because of assay sensitivity, timing of specimen collection, or specimen quality [11]. Factors involved in detecting and reporting cases may vary by age, geographically, over time, across healthcare settings, and by severity of disease. Finally, some people may be infected with SARS-CoV-2 and never show clinical symptoms; these asymptomatic persons would be even less likely to be detected [9, 10].
To better estimate the US incidence of SARS-CoV-2 infection since the beginning of the pandemic, we adapted a probabilistic multiplier model to adjust nationally reported counts of confirmed cases for various sources of underdetection [12]; this model estimates total SARS-CoV-2 infections, symptomatic illnesses, and hospitalized patients in the US population from 27 February 2020 to 30 September 2020.
METHODS
Reported Confirmed Cases
Persons with laboratory-confirmed SARS-CoV-2 infection by molecular diagnostics are reported to the Centers for Disease Control and Prevention (CDC) through the Nationally Notifiable Disease Surveillance System (NNDSS) at the person level or as aggregate counts at the reporting jurisdiction level (eg, state, territory, New York City, District of Columbia) [13, 14]. The NNDSS uses a standardized case report form, including state of residence, age, hospitalization admission, and other demographic and clinical characteristics. Given data entry delays and incomplete national reporting, jurisdictions reported aggregated counts daily for the previous day. Probable, asymptomatic, and travel-associated cases were excluded from counts of confirmed cases used in this analysis.
Analytic Methods
We applied a probabilistic multiplier model to adjust the reported numbers of confirmed symptomatic cases for factors affecting detection of persons with SARS-CoV-2 infection, a method previously used to estimate the incidence of H1N1pdm09 during the 2009 influenza pandemic [12]. This method uses confirmed cases and data on case detection and the asymptomatic fraction to estimate the cumulative number of hospitalized patients with SARS-CoV-2 infection, the total number with symptomatic illness, and the total number of infected persons (Figure 1).
To account for variability in detection of SARS-CoV-2 we stratified reported cases into hospitalized and nonhospitalized symptomatic cases, and further by age group (0–4 years, 5–17 years, 18–49 years, 50–64 years, ≥65 years), time period when the case was reported (February–March, April–May, June–July, August–September), and US Department of Health and Human Services (HHS) region [15]. Age group was imputed for cases with missing birth date according to the age distribution within each HHS region and reporting time period. If hospitalization status was missing, we imputed the percentage of patients who were hospitalized based on reported cases with complete data by age group, HHS region, and reporting time period. More details on this process are available in the Supplementary Methods.
We adjusted case counts for 3 factors that affected national case detection of symptomatic cases: if a patient is symptomatic, they may not have sought medical attention or testing for their illness (parameter C); if a patient sought medical care, they may not have had a SARS-CoV-2 test completed (parameter B); or if a patient was tested, the SARS-CoV-2 assay used may result in a false-negative result due to its sensitivity to detect SARS-CoV-2 in the specimen (parameter A). We used several data sources to describe these factors (Table 1), with underdetection multipliers calculated as an inverse of the product of factors A–C. Each multiplier was calculated within strata of hospitalization status, age group, and reporting time period, as data were available, and applied to the relevant stratified cases counts to estimate the number of symptomatic cases within that strata.
. | Parameter . | Data Source [reference] . | Observed Value . | Statistical Distribution Included in Model . |
---|---|---|---|---|
Hospitalized | ||||
A | SARS-CoV-2 assay sensitivity | Systematic review [16] | 2%–21% False-negative rate across included studies | Uniform (0.79, 0.98) (same values as non-hospitalized) |
B | SARS-CoV-2 test ordered and completed | IBM Watson and COVID Near You | Median (range): 0–17 years, 33% (15%–55%); 18–49 years, 50% (21%–96%); 50–64 years, 51% (18%–97%); ≥65 years, 54% (6%–98%) | Beta PERT, varies by age and date of case report (see Supplementary Table 1) (values specific to hospitalized settings) |
Nonhospitalized | ||||
A | SARS-CoV-2 assay sensitivity | Systematic review [16] | 2%–21% False-negative rate across included studies | Uniform (0.79, 0.98) (same values as hospitalized) |
B | SARS-CoV-2 test ordered and completed | IBM Watson and COVID Near You | Median (range): 0–17 years, 43% (1%–71%); 18–49 years, 53% (6%–99%); 50–64 years, 58% (6%–98%); ≥65 years, 54% (6%–99%) | Beta PERT, varies by age and date of case report (see Supplementary Table 1) (values specific to outpatient settings) |
C | Symptomatic patient seeks care | COVID Near You and Flu Near You | Median (range): 0–17 years, 26% (13%–49%); 18–49 years, 34% (15%–65%); 50–64 years, 35% (13%–55%); ≥65 years, 40% (11%–60%) | Beta PERT, varies by age and HHS region (see Supplementary Table 2) (values specific to outpatient settings) |
Total infections | ||||
D | Infected person is asymptomatic | [8, 17] | 0–64 years: 5%–24%; ≥65 years: 5%–32% | Uniform, varies by age |
. | Parameter . | Data Source [reference] . | Observed Value . | Statistical Distribution Included in Model . |
---|---|---|---|---|
Hospitalized | ||||
A | SARS-CoV-2 assay sensitivity | Systematic review [16] | 2%–21% False-negative rate across included studies | Uniform (0.79, 0.98) (same values as non-hospitalized) |
B | SARS-CoV-2 test ordered and completed | IBM Watson and COVID Near You | Median (range): 0–17 years, 33% (15%–55%); 18–49 years, 50% (21%–96%); 50–64 years, 51% (18%–97%); ≥65 years, 54% (6%–98%) | Beta PERT, varies by age and date of case report (see Supplementary Table 1) (values specific to hospitalized settings) |
Nonhospitalized | ||||
A | SARS-CoV-2 assay sensitivity | Systematic review [16] | 2%–21% False-negative rate across included studies | Uniform (0.79, 0.98) (same values as hospitalized) |
B | SARS-CoV-2 test ordered and completed | IBM Watson and COVID Near You | Median (range): 0–17 years, 43% (1%–71%); 18–49 years, 53% (6%–99%); 50–64 years, 58% (6%–98%); ≥65 years, 54% (6%–99%) | Beta PERT, varies by age and date of case report (see Supplementary Table 1) (values specific to outpatient settings) |
C | Symptomatic patient seeks care | COVID Near You and Flu Near You | Median (range): 0–17 years, 26% (13%–49%); 18–49 years, 34% (15%–65%); 50–64 years, 35% (13%–55%); ≥65 years, 40% (11%–60%) | Beta PERT, varies by age and HHS region (see Supplementary Table 2) (values specific to outpatient settings) |
Total infections | ||||
D | Infected person is asymptomatic | [8, 17] | 0–64 years: 5%–24%; ≥65 years: 5%–32% | Uniform, varies by age |
Abbreviations: COVID-19, coronavirus disease 2019; HHS, Department of Health and Human Services; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.
. | Parameter . | Data Source [reference] . | Observed Value . | Statistical Distribution Included in Model . |
---|---|---|---|---|
Hospitalized | ||||
A | SARS-CoV-2 assay sensitivity | Systematic review [16] | 2%–21% False-negative rate across included studies | Uniform (0.79, 0.98) (same values as non-hospitalized) |
B | SARS-CoV-2 test ordered and completed | IBM Watson and COVID Near You | Median (range): 0–17 years, 33% (15%–55%); 18–49 years, 50% (21%–96%); 50–64 years, 51% (18%–97%); ≥65 years, 54% (6%–98%) | Beta PERT, varies by age and date of case report (see Supplementary Table 1) (values specific to hospitalized settings) |
Nonhospitalized | ||||
A | SARS-CoV-2 assay sensitivity | Systematic review [16] | 2%–21% False-negative rate across included studies | Uniform (0.79, 0.98) (same values as hospitalized) |
B | SARS-CoV-2 test ordered and completed | IBM Watson and COVID Near You | Median (range): 0–17 years, 43% (1%–71%); 18–49 years, 53% (6%–99%); 50–64 years, 58% (6%–98%); ≥65 years, 54% (6%–99%) | Beta PERT, varies by age and date of case report (see Supplementary Table 1) (values specific to outpatient settings) |
C | Symptomatic patient seeks care | COVID Near You and Flu Near You | Median (range): 0–17 years, 26% (13%–49%); 18–49 years, 34% (15%–65%); 50–64 years, 35% (13%–55%); ≥65 years, 40% (11%–60%) | Beta PERT, varies by age and HHS region (see Supplementary Table 2) (values specific to outpatient settings) |
Total infections | ||||
D | Infected person is asymptomatic | [8, 17] | 0–64 years: 5%–24%; ≥65 years: 5%–32% | Uniform, varies by age |
. | Parameter . | Data Source [reference] . | Observed Value . | Statistical Distribution Included in Model . |
---|---|---|---|---|
Hospitalized | ||||
A | SARS-CoV-2 assay sensitivity | Systematic review [16] | 2%–21% False-negative rate across included studies | Uniform (0.79, 0.98) (same values as non-hospitalized) |
B | SARS-CoV-2 test ordered and completed | IBM Watson and COVID Near You | Median (range): 0–17 years, 33% (15%–55%); 18–49 years, 50% (21%–96%); 50–64 years, 51% (18%–97%); ≥65 years, 54% (6%–98%) | Beta PERT, varies by age and date of case report (see Supplementary Table 1) (values specific to hospitalized settings) |
Nonhospitalized | ||||
A | SARS-CoV-2 assay sensitivity | Systematic review [16] | 2%–21% False-negative rate across included studies | Uniform (0.79, 0.98) (same values as hospitalized) |
B | SARS-CoV-2 test ordered and completed | IBM Watson and COVID Near You | Median (range): 0–17 years, 43% (1%–71%); 18–49 years, 53% (6%–99%); 50–64 years, 58% (6%–98%); ≥65 years, 54% (6%–99%) | Beta PERT, varies by age and date of case report (see Supplementary Table 1) (values specific to outpatient settings) |
C | Symptomatic patient seeks care | COVID Near You and Flu Near You | Median (range): 0–17 years, 26% (13%–49%); 18–49 years, 34% (15%–65%); 50–64 years, 35% (13%–55%); ≥65 years, 40% (11%–60%) | Beta PERT, varies by age and HHS region (see Supplementary Table 2) (values specific to outpatient settings) |
Total infections | ||||
D | Infected person is asymptomatic | [8, 17] | 0–64 years: 5%–24%; ≥65 years: 5%–32% | Uniform, varies by age |
Abbreviations: COVID-19, coronavirus disease 2019; HHS, Department of Health and Human Services; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.
After adjustment, we summed the strata to a number of estimated symptomatic cases and applied one more source of underdetection—a person infected with SARS-CoV-2 may never show clinical symptoms (parameter D)—to estimate the number of total infections in the population.
For all parameters and strata, we included a range of values; estimates were calculated using Latin hypercube sampling with 10 000 iterations, with 95% uncertainty intervals (UIs) estimated as the 2.5th and 97.5th percentile range. Population rates were estimated using bridged-race population estimates from CDC Wonder [18]. Analyses were completed in R (version 3.6.1; R Foundation for Statistical Computing).
Sources of Underdetection of Cases
Parameter A. SARS-CoV-2 Assay Sensitivity
Patients infected with SARS-CoV-2 may not always test positive. Sensitivity of approved molecular diagnostic assays may be affected by the limits of detection of specific assays, specimen quality, source, handling, and timing of collection [11]. In a systematic review, 2%–21% of patients ultimately confirmed to have SARS-CoV-2 infection did not have a positive result unless multiple tests were performed over several days [16]. This review was used to estimate the probability that a specimen with SARS-CoV-2 will test positive (Table 1). For simplicity, since reported assay specificity has been high with false-positive results ranging between 1% and 4% [19, 20], we did not adjust for potential false positives.
Parameter B. SARS-CoV-2 Assay Ordered and Test Completed
Patients with SARS-CoV-2 infection who are not tested with molecular assays are not included in confirmed case counts. To characterize testing probabilities, we used data from 2 sources on healthcare visits and SARS-CoV-2 testing, and estimated this parameter separately for hospitalized and nonhospitalized patients. To capture the variability in testing practices across data sources, we represented this parameter using a beta PERT distribution centered on the median value and ranging between the minimum and maximum values reported across both data sources within each stratum of age (Table 1). The beta PERT distribution is a continuous probability distribution, which emphasizes the most likely values in an acceptable range of parameter values (ie, more often drawing closer to the middle value of the interval with a smaller probability on the extremes of the interval).
The first source of data was the IBM Watson Health Explorys electronic health record (EHR) database (IBM Corporation, Armonk, NY), which includes more than 39 health system partners across the country. We identified visits with an International Classification of Diseases, 10th revision (ICD-10), diagnosis or Systematized Nomenclature of Medicine Clinical Terms (SNOMED) code that indicated an acute respiratory illness (ARI) (Supplementary Table 7) and the number of those with evidence of SARS-CoV-2 test results from Logical Observation Identifiers Names and Codes (LOINC) codes for SARS-CoV-2 reverse transcription–polymerase chain reaction (RT-PCR) tests (Supplementary Table 8). For each setting (inpatient, outpatient, emergency department), visits and tests performed were aggregated into strata for time period and age group.
We also included rates of testing in the COVID Near You (CNY) survey platform. CNY is a website application where participants can self-report symptoms, healthcare-seeking behaviors, and SARS-CoV-2 testing information [21–23]. COVID-like illness (CLI) was defined using self-reported presence of shortness of breath or cough or 2 or more of self-reported fever, chills, sore throat, body ache, headache, or loss of taste or smell. Proportions of individuals who self-reported receiving a SARS-CoV-2 test among those who sought care for CLI were estimated for each time period with available data by HHS region and age group (Table 1, Supplementary Table 1).
Parameter C. Symptomatic Patient Seeks Care/Testing
A symptomatic person with SARS-CoV-2 infection will not be included in confirmed case counts if they never sought medical attention or testing services. To estimate healthcare seeking, we used data obtained from both CNY and Flu Near You (FNY) [24], which has conducted participatory surveillance for influenza-like illnesses since 2011, to better capture the full time period and differences between participants of the 2 systems. We considered a range of symptomatic illness including the following: (1) CLI as described above, but excluding loss of taste or smell for FNY, which was not captured in that platform; (2) a more specific case definition of fever, and either cough or shortness of breath; and (3) a broader case definition of at least 1 of fever, cough, or shortness of breath. Among patients who met the given case definition, we calculated the proportion who reported visiting a doctor’s office, urgent care clinic, outpatient clinic, emergency department, testing center, telemedicine, or other healthcare setting for symptoms. Care-seeking proportions were included using a beta PERT distribution of the median and range of values across the 3 case definitions and 2 data sources, stratified by report date and age group (Table 1, Supplementary Table 2).
Parameter D. Patient Is Symptomatic if Infected With SARS-CoV-2
Some people infected with SARS-CoV-2 do not experience symptoms [25]. To estimate the number of infections in the population, we adjusted the sum of hospitalized and symptomatic nonhospitalized cases based on the proportion of persons with confirmed COVID-19 and no symptoms from a meta-analysis of available literature (Table 1) [17].
RESULTS
National Case Reporting
During 27 February–30 September 2020, there were 6 891 764 confirmed cases of symptomatic COVID-19 acquired domestically and reported nationally through individual or aggregate case counts. We estimated that approximately 14% of these patients had been hospitalized, with variation by age group, case report date, and HHS region (Table 2).
. | Reported Cases, n . | Rate of Reported Cases, per 100 000 Populationa . | Percentage of Reported Cases Hospitalized, Medianb,c . | Rate of Reported Hospitalization, Median, per 100 000 Populationa,b . |
---|---|---|---|---|
Total | 6 891 764 | 2106 | 14 | 296 |
Age group (years) | ||||
0–4 | 109 317 | 552 | 6 | 31 |
5–17 | 458 552 | 856 | 3 | 26 |
18–49 | 3 974 817 | 2877 | 7 | 195 |
50–64 | 1 377 416 | 2181 | 19 | 418 |
≥65 | 971 662 | 1853 | 43 | 789 |
HHS region | ||||
1 (CT, MA, ME, NH, RI, VT) | 208 808 | 1406 | 19 | 271 |
2 (NJ, NY, PR, VI)c | 679 581 | 2389 | 33 | 786 |
3 (DE, DC, MD, PA, VA, WV) | 468 065 | 1518 | 14 | 208 |
4 (AL, FL, GA, KY, MS, NC, SC, TN) | 1 769 052 | 2664 | 9 | 241 |
5 (IL, IN, MI, MN, OH, WI) | 882 355 | 1679 | 15 | 258 |
6 (AR, LA, NM, OK, TX) | 1 092 515 | 2576 | 12 | 312 |
7 (IA, KS, MO, NE) | 308 636 | 2185 | 8 | 174 |
8 (CO, MT, ND, SD, UT, WY) | 200 390 | 1651 | 7 | 123 |
9 (AZ, CA, HI, NV, AS, MP, FSM, GU, RMI, PW) | 1 117 180 | 2183 | 14 | 310 |
10 (AK, ID, OR, WA) | 165 182 | 1162 | 8 | 92 |
. | Reported Cases, n . | Rate of Reported Cases, per 100 000 Populationa . | Percentage of Reported Cases Hospitalized, Medianb,c . | Rate of Reported Hospitalization, Median, per 100 000 Populationa,b . |
---|---|---|---|---|
Total | 6 891 764 | 2106 | 14 | 296 |
Age group (years) | ||||
0–4 | 109 317 | 552 | 6 | 31 |
5–17 | 458 552 | 856 | 3 | 26 |
18–49 | 3 974 817 | 2877 | 7 | 195 |
50–64 | 1 377 416 | 2181 | 19 | 418 |
≥65 | 971 662 | 1853 | 43 | 789 |
HHS region | ||||
1 (CT, MA, ME, NH, RI, VT) | 208 808 | 1406 | 19 | 271 |
2 (NJ, NY, PR, VI)c | 679 581 | 2389 | 33 | 786 |
3 (DE, DC, MD, PA, VA, WV) | 468 065 | 1518 | 14 | 208 |
4 (AL, FL, GA, KY, MS, NC, SC, TN) | 1 769 052 | 2664 | 9 | 241 |
5 (IL, IN, MI, MN, OH, WI) | 882 355 | 1679 | 15 | 258 |
6 (AR, LA, NM, OK, TX) | 1 092 515 | 2576 | 12 | 312 |
7 (IA, KS, MO, NE) | 308 636 | 2185 | 8 | 174 |
8 (CO, MT, ND, SD, UT, WY) | 200 390 | 1651 | 7 | 123 |
9 (AZ, CA, HI, NV, AS, MP, FSM, GU, RMI, PW) | 1 117 180 | 2183 | 14 | 310 |
10 (AK, ID, OR, WA) | 165 182 | 1162 | 8 | 92 |
Patient age was imputed if missing (17% of cases).Abbreviations: AS, American Samoa; CDC, Centers for Disease Control and Prevention; COVID-19, coronavirus disease 2019; FSM, Federated States of Micronesia; GU, Guam; HHS, Department of Health and Human Services; MP, Northern Mariana Islands; NYC, New York City; PR, Puerto Rico PW, Palau; RMI, Marshall Islands; VI, US Virgin Islands.
aPopulation estimated using CDC Wonder Bridged-Race estimates [18].
bPatient hospitalization status imputed if missing (86% of cases).
cFor hospitalization imputation, the regional proportion of cases reported as hospitalized in region 2 was estimated excluding NYC due to a large discrepancy between national and jurisdiction reports.
. | Reported Cases, n . | Rate of Reported Cases, per 100 000 Populationa . | Percentage of Reported Cases Hospitalized, Medianb,c . | Rate of Reported Hospitalization, Median, per 100 000 Populationa,b . |
---|---|---|---|---|
Total | 6 891 764 | 2106 | 14 | 296 |
Age group (years) | ||||
0–4 | 109 317 | 552 | 6 | 31 |
5–17 | 458 552 | 856 | 3 | 26 |
18–49 | 3 974 817 | 2877 | 7 | 195 |
50–64 | 1 377 416 | 2181 | 19 | 418 |
≥65 | 971 662 | 1853 | 43 | 789 |
HHS region | ||||
1 (CT, MA, ME, NH, RI, VT) | 208 808 | 1406 | 19 | 271 |
2 (NJ, NY, PR, VI)c | 679 581 | 2389 | 33 | 786 |
3 (DE, DC, MD, PA, VA, WV) | 468 065 | 1518 | 14 | 208 |
4 (AL, FL, GA, KY, MS, NC, SC, TN) | 1 769 052 | 2664 | 9 | 241 |
5 (IL, IN, MI, MN, OH, WI) | 882 355 | 1679 | 15 | 258 |
6 (AR, LA, NM, OK, TX) | 1 092 515 | 2576 | 12 | 312 |
7 (IA, KS, MO, NE) | 308 636 | 2185 | 8 | 174 |
8 (CO, MT, ND, SD, UT, WY) | 200 390 | 1651 | 7 | 123 |
9 (AZ, CA, HI, NV, AS, MP, FSM, GU, RMI, PW) | 1 117 180 | 2183 | 14 | 310 |
10 (AK, ID, OR, WA) | 165 182 | 1162 | 8 | 92 |
. | Reported Cases, n . | Rate of Reported Cases, per 100 000 Populationa . | Percentage of Reported Cases Hospitalized, Medianb,c . | Rate of Reported Hospitalization, Median, per 100 000 Populationa,b . |
---|---|---|---|---|
Total | 6 891 764 | 2106 | 14 | 296 |
Age group (years) | ||||
0–4 | 109 317 | 552 | 6 | 31 |
5–17 | 458 552 | 856 | 3 | 26 |
18–49 | 3 974 817 | 2877 | 7 | 195 |
50–64 | 1 377 416 | 2181 | 19 | 418 |
≥65 | 971 662 | 1853 | 43 | 789 |
HHS region | ||||
1 (CT, MA, ME, NH, RI, VT) | 208 808 | 1406 | 19 | 271 |
2 (NJ, NY, PR, VI)c | 679 581 | 2389 | 33 | 786 |
3 (DE, DC, MD, PA, VA, WV) | 468 065 | 1518 | 14 | 208 |
4 (AL, FL, GA, KY, MS, NC, SC, TN) | 1 769 052 | 2664 | 9 | 241 |
5 (IL, IN, MI, MN, OH, WI) | 882 355 | 1679 | 15 | 258 |
6 (AR, LA, NM, OK, TX) | 1 092 515 | 2576 | 12 | 312 |
7 (IA, KS, MO, NE) | 308 636 | 2185 | 8 | 174 |
8 (CO, MT, ND, SD, UT, WY) | 200 390 | 1651 | 7 | 123 |
9 (AZ, CA, HI, NV, AS, MP, FSM, GU, RMI, PW) | 1 117 180 | 2183 | 14 | 310 |
10 (AK, ID, OR, WA) | 165 182 | 1162 | 8 | 92 |
Patient age was imputed if missing (17% of cases).Abbreviations: AS, American Samoa; CDC, Centers for Disease Control and Prevention; COVID-19, coronavirus disease 2019; FSM, Federated States of Micronesia; GU, Guam; HHS, Department of Health and Human Services; MP, Northern Mariana Islands; NYC, New York City; PR, Puerto Rico PW, Palau; RMI, Marshall Islands; VI, US Virgin Islands.
aPopulation estimated using CDC Wonder Bridged-Race estimates [18].
bPatient hospitalization status imputed if missing (86% of cases).
cFor hospitalization imputation, the regional proportion of cases reported as hospitalized in region 2 was estimated excluding NYC due to a large discrepancy between national and jurisdiction reports.
Hospitalized Cases
We estimated 2.5 (95% UI: 2.0–3.1) SARS-CoV-2 hospitalizations in the population for each hospitalized case reported nationally, with variations by age group, HHS region, and report date. Underdetection multipliers decreased over time and were consistently highest among children (Supplementary Table 3).
Adjusting case counts by HHS region, age group, and report date, we estimated a total of 2 397 777 (95% UI: 2 053 156–2 855 843) hospitalizations with SARS-CoV-2 infection (Table 3), or 733 hospitalizations per 100 000 population. The highest rates of hospitalization were among patients aged 65 years and older (1950/100 000) and lowest among children 5–17 years of age (83/100 000). Estimates varied geographically: 236 per 100 000 in HHS region 10 to 2440 per 100 000 in HHS region 2.
. | Estimated Hospitalizations . | 95% UI . | Rate, per 100 000a . | 95% UI . |
---|---|---|---|---|
Overallb | 2 397 777 | 2 053 156–2 855 843 | 733 | 628–873 |
Age group (years) | ||||
0–4 | 20 719 | 16 595–26 069 | 105 | 84–132 |
5–17 | 44 321 | 33 300–58 552 | 83 | 62–109 |
18–49 | 652 741 | 530 955–823 453 | 472 | 384–596 |
50–64 | 642 358 | 538 092–778 266 | 1017 | 852–1232 |
≥65 | 1 022 295 | 826 438–1 361 730 | 1950 | 1576–2597 |
HHS region | ||||
1 (CT, MA, ME, NH, RI, VT) | 103 347 | 86 983–125 978 | 696 | 586–848 |
2 (NJ, NY, PR, VI)c | 694 079 | 580 828–878 399 | 2440 | 2042–3087 |
3 (DE, DC, MD, PA, VA, WV) | 152 597 | 129 196–181 597 | 495 | 419–589 |
4 (AL, FL, GA, KY, MS, NC, SC, TN) | 349 780 | 289 336–423 126 | 527 | 436–637 |
5 (IL, IN, MI, MN, OH, WI) | 330 948 | 278 985–395 956 | 630 | 531–754 |
6 (AR, LA, NM, OK, TX) | 288 441 | 231 390–357 417 | 680 | 546–843 |
7 (IA, KS, MO, NE) | 55 692 | 45 600–68 225 | 394 | 323–483 |
8 (CO, MT, ND, SD, UT, WY) | 39 413 | 33 449–47 559 | 325 | 276–392 |
9 (AZ, CA, HI, NV, AS, MP, FSM, GU, RMI, PW) | 347 069 | 291 807–414 925 | 678 | 570–811 |
10 (AK, ID, OR, WA) | 33 552 | 28 430–41 594 | 236 | 200–293 |
. | Estimated Hospitalizations . | 95% UI . | Rate, per 100 000a . | 95% UI . |
---|---|---|---|---|
Overallb | 2 397 777 | 2 053 156–2 855 843 | 733 | 628–873 |
Age group (years) | ||||
0–4 | 20 719 | 16 595–26 069 | 105 | 84–132 |
5–17 | 44 321 | 33 300–58 552 | 83 | 62–109 |
18–49 | 652 741 | 530 955–823 453 | 472 | 384–596 |
50–64 | 642 358 | 538 092–778 266 | 1017 | 852–1232 |
≥65 | 1 022 295 | 826 438–1 361 730 | 1950 | 1576–2597 |
HHS region | ||||
1 (CT, MA, ME, NH, RI, VT) | 103 347 | 86 983–125 978 | 696 | 586–848 |
2 (NJ, NY, PR, VI)c | 694 079 | 580 828–878 399 | 2440 | 2042–3087 |
3 (DE, DC, MD, PA, VA, WV) | 152 597 | 129 196–181 597 | 495 | 419–589 |
4 (AL, FL, GA, KY, MS, NC, SC, TN) | 349 780 | 289 336–423 126 | 527 | 436–637 |
5 (IL, IN, MI, MN, OH, WI) | 330 948 | 278 985–395 956 | 630 | 531–754 |
6 (AR, LA, NM, OK, TX) | 288 441 | 231 390–357 417 | 680 | 546–843 |
7 (IA, KS, MO, NE) | 55 692 | 45 600–68 225 | 394 | 323–483 |
8 (CO, MT, ND, SD, UT, WY) | 39 413 | 33 449–47 559 | 325 | 276–392 |
9 (AZ, CA, HI, NV, AS, MP, FSM, GU, RMI, PW) | 347 069 | 291 807–414 925 | 678 | 570–811 |
10 (AK, ID, OR, WA) | 33 552 | 28 430–41 594 | 236 | 200–293 |
Abbreviations: AS, American Samoa; CDC, Centers for Disease Control and Prevention; COVID-19, coronavirus disease 2019; FSM, Federated States of Micronesia; GU, Guam; HHS, Department of Health and Human Services; MP, Northern Mariana Islands; NYC, New York City; PR, Puerto Rico; PW, Palau; RMI, Marshall Islands UI, uncertainty interval.
aPopulation estimated using CDC Wonder Bridged-Race estimates [18].
bDue to rounding, age group and region estimates may not sum to overall estimates.
cFor hospitalization imputation, the regional proportion of cases reported as hospitalized in region 2 was estimated excluding NYC due to a large discrepancy between national and jurisdiction reports.
. | Estimated Hospitalizations . | 95% UI . | Rate, per 100 000a . | 95% UI . |
---|---|---|---|---|
Overallb | 2 397 777 | 2 053 156–2 855 843 | 733 | 628–873 |
Age group (years) | ||||
0–4 | 20 719 | 16 595–26 069 | 105 | 84–132 |
5–17 | 44 321 | 33 300–58 552 | 83 | 62–109 |
18–49 | 652 741 | 530 955–823 453 | 472 | 384–596 |
50–64 | 642 358 | 538 092–778 266 | 1017 | 852–1232 |
≥65 | 1 022 295 | 826 438–1 361 730 | 1950 | 1576–2597 |
HHS region | ||||
1 (CT, MA, ME, NH, RI, VT) | 103 347 | 86 983–125 978 | 696 | 586–848 |
2 (NJ, NY, PR, VI)c | 694 079 | 580 828–878 399 | 2440 | 2042–3087 |
3 (DE, DC, MD, PA, VA, WV) | 152 597 | 129 196–181 597 | 495 | 419–589 |
4 (AL, FL, GA, KY, MS, NC, SC, TN) | 349 780 | 289 336–423 126 | 527 | 436–637 |
5 (IL, IN, MI, MN, OH, WI) | 330 948 | 278 985–395 956 | 630 | 531–754 |
6 (AR, LA, NM, OK, TX) | 288 441 | 231 390–357 417 | 680 | 546–843 |
7 (IA, KS, MO, NE) | 55 692 | 45 600–68 225 | 394 | 323–483 |
8 (CO, MT, ND, SD, UT, WY) | 39 413 | 33 449–47 559 | 325 | 276–392 |
9 (AZ, CA, HI, NV, AS, MP, FSM, GU, RMI, PW) | 347 069 | 291 807–414 925 | 678 | 570–811 |
10 (AK, ID, OR, WA) | 33 552 | 28 430–41 594 | 236 | 200–293 |
. | Estimated Hospitalizations . | 95% UI . | Rate, per 100 000a . | 95% UI . |
---|---|---|---|---|
Overallb | 2 397 777 | 2 053 156–2 855 843 | 733 | 628–873 |
Age group (years) | ||||
0–4 | 20 719 | 16 595–26 069 | 105 | 84–132 |
5–17 | 44 321 | 33 300–58 552 | 83 | 62–109 |
18–49 | 652 741 | 530 955–823 453 | 472 | 384–596 |
50–64 | 642 358 | 538 092–778 266 | 1017 | 852–1232 |
≥65 | 1 022 295 | 826 438–1 361 730 | 1950 | 1576–2597 |
HHS region | ||||
1 (CT, MA, ME, NH, RI, VT) | 103 347 | 86 983–125 978 | 696 | 586–848 |
2 (NJ, NY, PR, VI)c | 694 079 | 580 828–878 399 | 2440 | 2042–3087 |
3 (DE, DC, MD, PA, VA, WV) | 152 597 | 129 196–181 597 | 495 | 419–589 |
4 (AL, FL, GA, KY, MS, NC, SC, TN) | 349 780 | 289 336–423 126 | 527 | 436–637 |
5 (IL, IN, MI, MN, OH, WI) | 330 948 | 278 985–395 956 | 630 | 531–754 |
6 (AR, LA, NM, OK, TX) | 288 441 | 231 390–357 417 | 680 | 546–843 |
7 (IA, KS, MO, NE) | 55 692 | 45 600–68 225 | 394 | 323–483 |
8 (CO, MT, ND, SD, UT, WY) | 39 413 | 33 449–47 559 | 325 | 276–392 |
9 (AZ, CA, HI, NV, AS, MP, FSM, GU, RMI, PW) | 347 069 | 291 807–414 925 | 678 | 570–811 |
10 (AK, ID, OR, WA) | 33 552 | 28 430–41 594 | 236 | 200–293 |
Abbreviations: AS, American Samoa; CDC, Centers for Disease Control and Prevention; COVID-19, coronavirus disease 2019; FSM, Federated States of Micronesia; GU, Guam; HHS, Department of Health and Human Services; MP, Northern Mariana Islands; NYC, New York City; PR, Puerto Rico; PW, Palau; RMI, Marshall Islands UI, uncertainty interval.
aPopulation estimated using CDC Wonder Bridged-Race estimates [18].
bDue to rounding, age group and region estimates may not sum to overall estimates.
cFor hospitalization imputation, the regional proportion of cases reported as hospitalized in region 2 was estimated excluding NYC due to a large discrepancy between national and jurisdiction reports.
Nonhospitalized Symptomatic Illnesses
We estimated 7.1 (95% UI: 5.8–9.0) nonhospitalized symptomatic illnesses for every 1 nonhospitalized case reported nationally, with variation by age group, HHS region, and report date. Underdetection multipliers decreased over time and were consistently highest among children (Supplementary Table 3).
We summed the estimated hospitalized (Table 3) and nonhospitalized (Supplementary Table 5) illnesses for a total of 44.8 million symptomatic illnesses (Table 4). The highest rates of symptomatic illness were among adults 18–49 years old (18 162/100 000) and were lowest among children aged 0–4 years (5777/100 000). Estimates varied geographically: 8282 per 100 000 in HHS region 10 to 26 705 per 100 000 in HHS region 2.
. | Estimated Symptomatic Illnesses . | 95% UI . | Rate, per 100 000a . | 95% UI . |
---|---|---|---|---|
Overallb | 44 769 417 | 36 920 353–55 535 659 | 13 684 | 11 285–16 975 |
Age group (years) | ||||
0–4 | 1 144 532 | 903 194–1 500 315 | 5777 | 4559–7573 |
5–17 | 4 719 785 | 3 722 649–6 177 733 | 8807 | 6947–11 528 |
18–49 | 25 096 725 | 19 137 381–34 524 124 | 18 162 | 13 850–24 985 |
50–64 | 8 926 318 | 6 873 250–11 928 318 | 14 133 | 10 883–18 887 |
≥65 | 4 556 384 | 3 569 223–6 172 269 | 8690 | 6807–11 772 |
HHS region | ||||
1 (CT, MA, ME, NH, RI, VT) | 1 613 724 | 1 321 058–2 018 578 | 10 864 | 8894–13 590 |
2 (NJ, NY, PR, VI) | 7 597 800 | 5 828 412–10 470 229 | 26 705 | 20 486–36 801 |
3 (DE, DC, MD, PA, VA, WV) | 3 179 080 | 2 627 466–3 915 693 | 10 307 | 8519–12 696 |
4 (AL, FL, GA, KY, MS, NC, SC, TN) | 10 263 209 | 8 428 418–12 805 689 | 15 457 | 12 694–19 286 |
5 (IL, IN, MI, MN, OH, WI) | 5 351 673 | 4 327 360–6 904 494 | 10 185 | 8236–13 141 |
6 (AR, LA, NM, OK, TX) | 6 200 307 | 5 074 596–7 815 354 | 14 618 | 11 964–18 426 |
7 (IA, KS, MO, NE) | 1 796 811 | 1 456 136–2 307 574 | 12 722 | 10 310–16 339 |
8 (CO, MT, ND, SD, UT, WY) | 1 329 434 | 1 087 300–1 676 711 | 10 952 | 8957–13 813 |
9 (AZ, CA, HI, NV, AS, MP, FSM, GU, RMI, PW) | 6 155 322 | 5 093 684–7 539 673 | 12 026 | 9952–14 731 |
10 (AK, ID, OR, WA) | 1 177 495 | 956 766–1 476 146 | 8282 | 6729–10 382 |
. | Estimated Symptomatic Illnesses . | 95% UI . | Rate, per 100 000a . | 95% UI . |
---|---|---|---|---|
Overallb | 44 769 417 | 36 920 353–55 535 659 | 13 684 | 11 285–16 975 |
Age group (years) | ||||
0–4 | 1 144 532 | 903 194–1 500 315 | 5777 | 4559–7573 |
5–17 | 4 719 785 | 3 722 649–6 177 733 | 8807 | 6947–11 528 |
18–49 | 25 096 725 | 19 137 381–34 524 124 | 18 162 | 13 850–24 985 |
50–64 | 8 926 318 | 6 873 250–11 928 318 | 14 133 | 10 883–18 887 |
≥65 | 4 556 384 | 3 569 223–6 172 269 | 8690 | 6807–11 772 |
HHS region | ||||
1 (CT, MA, ME, NH, RI, VT) | 1 613 724 | 1 321 058–2 018 578 | 10 864 | 8894–13 590 |
2 (NJ, NY, PR, VI) | 7 597 800 | 5 828 412–10 470 229 | 26 705 | 20 486–36 801 |
3 (DE, DC, MD, PA, VA, WV) | 3 179 080 | 2 627 466–3 915 693 | 10 307 | 8519–12 696 |
4 (AL, FL, GA, KY, MS, NC, SC, TN) | 10 263 209 | 8 428 418–12 805 689 | 15 457 | 12 694–19 286 |
5 (IL, IN, MI, MN, OH, WI) | 5 351 673 | 4 327 360–6 904 494 | 10 185 | 8236–13 141 |
6 (AR, LA, NM, OK, TX) | 6 200 307 | 5 074 596–7 815 354 | 14 618 | 11 964–18 426 |
7 (IA, KS, MO, NE) | 1 796 811 | 1 456 136–2 307 574 | 12 722 | 10 310–16 339 |
8 (CO, MT, ND, SD, UT, WY) | 1 329 434 | 1 087 300–1 676 711 | 10 952 | 8957–13 813 |
9 (AZ, CA, HI, NV, AS, MP, FSM, GU, RMI, PW) | 6 155 322 | 5 093 684–7 539 673 | 12 026 | 9952–14 731 |
10 (AK, ID, OR, WA) | 1 177 495 | 956 766–1 476 146 | 8282 | 6729–10 382 |
Abbreviations: AS, American Samoa; CDC, Centers for Disease Control and Prevention; FSM, Federated States of Micronesia; GU, Guam; HHS, Department of Health and Human Services; MP, Northern Mariana Islands; PR, Puerto Rico; PW, Palau; RMI, Marshall Islands; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; UI, uncertainty interval; VI, US Virgin Islands.
aPopulation estimated using CDC Wonder Bridged-Race estimates [18].
bDue to rounding, age group and region estimates may not sum to overall estimates.
. | Estimated Symptomatic Illnesses . | 95% UI . | Rate, per 100 000a . | 95% UI . |
---|---|---|---|---|
Overallb | 44 769 417 | 36 920 353–55 535 659 | 13 684 | 11 285–16 975 |
Age group (years) | ||||
0–4 | 1 144 532 | 903 194–1 500 315 | 5777 | 4559–7573 |
5–17 | 4 719 785 | 3 722 649–6 177 733 | 8807 | 6947–11 528 |
18–49 | 25 096 725 | 19 137 381–34 524 124 | 18 162 | 13 850–24 985 |
50–64 | 8 926 318 | 6 873 250–11 928 318 | 14 133 | 10 883–18 887 |
≥65 | 4 556 384 | 3 569 223–6 172 269 | 8690 | 6807–11 772 |
HHS region | ||||
1 (CT, MA, ME, NH, RI, VT) | 1 613 724 | 1 321 058–2 018 578 | 10 864 | 8894–13 590 |
2 (NJ, NY, PR, VI) | 7 597 800 | 5 828 412–10 470 229 | 26 705 | 20 486–36 801 |
3 (DE, DC, MD, PA, VA, WV) | 3 179 080 | 2 627 466–3 915 693 | 10 307 | 8519–12 696 |
4 (AL, FL, GA, KY, MS, NC, SC, TN) | 10 263 209 | 8 428 418–12 805 689 | 15 457 | 12 694–19 286 |
5 (IL, IN, MI, MN, OH, WI) | 5 351 673 | 4 327 360–6 904 494 | 10 185 | 8236–13 141 |
6 (AR, LA, NM, OK, TX) | 6 200 307 | 5 074 596–7 815 354 | 14 618 | 11 964–18 426 |
7 (IA, KS, MO, NE) | 1 796 811 | 1 456 136–2 307 574 | 12 722 | 10 310–16 339 |
8 (CO, MT, ND, SD, UT, WY) | 1 329 434 | 1 087 300–1 676 711 | 10 952 | 8957–13 813 |
9 (AZ, CA, HI, NV, AS, MP, FSM, GU, RMI, PW) | 6 155 322 | 5 093 684–7 539 673 | 12 026 | 9952–14 731 |
10 (AK, ID, OR, WA) | 1 177 495 | 956 766–1 476 146 | 8282 | 6729–10 382 |
. | Estimated Symptomatic Illnesses . | 95% UI . | Rate, per 100 000a . | 95% UI . |
---|---|---|---|---|
Overallb | 44 769 417 | 36 920 353–55 535 659 | 13 684 | 11 285–16 975 |
Age group (years) | ||||
0–4 | 1 144 532 | 903 194–1 500 315 | 5777 | 4559–7573 |
5–17 | 4 719 785 | 3 722 649–6 177 733 | 8807 | 6947–11 528 |
18–49 | 25 096 725 | 19 137 381–34 524 124 | 18 162 | 13 850–24 985 |
50–64 | 8 926 318 | 6 873 250–11 928 318 | 14 133 | 10 883–18 887 |
≥65 | 4 556 384 | 3 569 223–6 172 269 | 8690 | 6807–11 772 |
HHS region | ||||
1 (CT, MA, ME, NH, RI, VT) | 1 613 724 | 1 321 058–2 018 578 | 10 864 | 8894–13 590 |
2 (NJ, NY, PR, VI) | 7 597 800 | 5 828 412–10 470 229 | 26 705 | 20 486–36 801 |
3 (DE, DC, MD, PA, VA, WV) | 3 179 080 | 2 627 466–3 915 693 | 10 307 | 8519–12 696 |
4 (AL, FL, GA, KY, MS, NC, SC, TN) | 10 263 209 | 8 428 418–12 805 689 | 15 457 | 12 694–19 286 |
5 (IL, IN, MI, MN, OH, WI) | 5 351 673 | 4 327 360–6 904 494 | 10 185 | 8236–13 141 |
6 (AR, LA, NM, OK, TX) | 6 200 307 | 5 074 596–7 815 354 | 14 618 | 11 964–18 426 |
7 (IA, KS, MO, NE) | 1 796 811 | 1 456 136–2 307 574 | 12 722 | 10 310–16 339 |
8 (CO, MT, ND, SD, UT, WY) | 1 329 434 | 1 087 300–1 676 711 | 10 952 | 8957–13 813 |
9 (AZ, CA, HI, NV, AS, MP, FSM, GU, RMI, PW) | 6 155 322 | 5 093 684–7 539 673 | 12 026 | 9952–14 731 |
10 (AK, ID, OR, WA) | 1 177 495 | 956 766–1 476 146 | 8282 | 6729–10 382 |
Abbreviations: AS, American Samoa; CDC, Centers for Disease Control and Prevention; FSM, Federated States of Micronesia; GU, Guam; HHS, Department of Health and Human Services; MP, Northern Mariana Islands; PR, Puerto Rico; PW, Palau; RMI, Marshall Islands; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; UI, uncertainty interval; VI, US Virgin Islands.
aPopulation estimated using CDC Wonder Bridged-Race estimates [18].
bDue to rounding, age group and region estimates may not sum to overall estimates.
Total Infections
Using age-stratified estimates of the proportion of infections that remain asymptomatic, we estimated that the nationally reported cases during February–September may represent a total of 52 885 526 (95% UI: 42 527 569–66 810 205) SARS-CoV-2 infections in the US population, with the highest infection rates among persons aged 18–49 years (Table 5). This indicates that 1 in 7.7, or 13%, of total infections were identified and reported. Detection varied by age, with lower detection rates among children, but with improvements over time (Supplementary Table 4).
. | Estimated Total Infections . | 95% UI . | Rate, per 100 000a . | 95% UI . |
---|---|---|---|---|
Overallb | 52 885 526 | 42 527 569–66 810 205 | 16 165 | 12 999–20 421 |
Age group (years) | ||||
0–4 | 1 342 212 | 1 022 465–1 811 583 | 6775 | 5161–9145 |
5–17 | 5 538 766 | 4 222 053–7 451 900 | 10 336 | 7879–13 906 |
18–49 | 29 421 481 | 21 798 393–41 330 693 | 21 292 | 15 775–29 911 |
50–64 | 10 484 802 | 7 860 849–14 346 364 | 16 601 | 12 446–22 715 |
≥65 | 5 636 607 | 4 139 528–8 024 420 | 10 750 | 7895–15 305 |
HHS region | ||||
1 (CT, MA, ME, NH, RI, VT) | 1 910 156 | 1 530 556–2 427 485 | 12 860 | 10 304–16 343 |
2 (NJ, NY, PR, VI) | 8 977 706 | 6 780 805–12 534 610 | 31 555 | 23 834–44 057 |
3 (DE, DC, MD, PA, VA, WV) | 3 759 656 | 3 025 633–4 721 730 | 12 190 | 9810–15 309 |
4 (AL, FL, GA, KY, MS, NC, SC, TN) | 12 107 021 | 9 741 202–15 448 374 | 18 234 | 14 671–23 266 |
5 (IL, IN, MI, MN, OH, WI) | 6 324 790 | 5 002 112–8 272 471 | 12 037 | 9520–15 744 |
6 (AR, LA, NM, OK, TX) | 7 315 403 | 5 856 636–9 423 602 | 17 248 | 13 808–22 218 |
7 (IA, KS, MO, NE) | 2 122 340 | 1 684 158–2 788 524 | 15 027 | 11 925–19 744 |
8 (CO, MT, ND, SD, UT, WY) | 1 569 175 | 1 250 443–2 013 970 | 12 927 | 10 301–16 591 |
9 (AZ, CA, HI, NV, AS, MP, FSM, GU, RMI, PW) | 7 243 925 | 5 876 211–9 098 261 | 14 153 | 11 481–17 776 |
10 (AK, ID, OR, WA) | 1 391 488 | 1 106 862–1 775 644 | 9787 | 7785–12 489 |
. | Estimated Total Infections . | 95% UI . | Rate, per 100 000a . | 95% UI . |
---|---|---|---|---|
Overallb | 52 885 526 | 42 527 569–66 810 205 | 16 165 | 12 999–20 421 |
Age group (years) | ||||
0–4 | 1 342 212 | 1 022 465–1 811 583 | 6775 | 5161–9145 |
5–17 | 5 538 766 | 4 222 053–7 451 900 | 10 336 | 7879–13 906 |
18–49 | 29 421 481 | 21 798 393–41 330 693 | 21 292 | 15 775–29 911 |
50–64 | 10 484 802 | 7 860 849–14 346 364 | 16 601 | 12 446–22 715 |
≥65 | 5 636 607 | 4 139 528–8 024 420 | 10 750 | 7895–15 305 |
HHS region | ||||
1 (CT, MA, ME, NH, RI, VT) | 1 910 156 | 1 530 556–2 427 485 | 12 860 | 10 304–16 343 |
2 (NJ, NY, PR, VI) | 8 977 706 | 6 780 805–12 534 610 | 31 555 | 23 834–44 057 |
3 (DE, DC, MD, PA, VA, WV) | 3 759 656 | 3 025 633–4 721 730 | 12 190 | 9810–15 309 |
4 (AL, FL, GA, KY, MS, NC, SC, TN) | 12 107 021 | 9 741 202–15 448 374 | 18 234 | 14 671–23 266 |
5 (IL, IN, MI, MN, OH, WI) | 6 324 790 | 5 002 112–8 272 471 | 12 037 | 9520–15 744 |
6 (AR, LA, NM, OK, TX) | 7 315 403 | 5 856 636–9 423 602 | 17 248 | 13 808–22 218 |
7 (IA, KS, MO, NE) | 2 122 340 | 1 684 158–2 788 524 | 15 027 | 11 925–19 744 |
8 (CO, MT, ND, SD, UT, WY) | 1 569 175 | 1 250 443–2 013 970 | 12 927 | 10 301–16 591 |
9 (AZ, CA, HI, NV, AS, MP, FSM, GU, RMI, PW) | 7 243 925 | 5 876 211–9 098 261 | 14 153 | 11 481–17 776 |
10 (AK, ID, OR, WA) | 1 391 488 | 1 106 862–1 775 644 | 9787 | 7785–12 489 |
Abbreviations: AS, American Samoa; CDC, Centers for Disease Control and Prevention; FSM, Federated States of Micronesia; GU, Guam; HHS, Department of Health and Human Services; MP, Northern Mariana Islands; PR, Puerto Rico; PW, Palau; RMI, Marshall Islands; UI, uncertainty interval; VI, US Virgin Islands.
aPopulation estimated using CDC Wonder Bridged-Race estimates [18].
bDue to rounding, age group and region estimates may not sum to overall estimates.
. | Estimated Total Infections . | 95% UI . | Rate, per 100 000a . | 95% UI . |
---|---|---|---|---|
Overallb | 52 885 526 | 42 527 569–66 810 205 | 16 165 | 12 999–20 421 |
Age group (years) | ||||
0–4 | 1 342 212 | 1 022 465–1 811 583 | 6775 | 5161–9145 |
5–17 | 5 538 766 | 4 222 053–7 451 900 | 10 336 | 7879–13 906 |
18–49 | 29 421 481 | 21 798 393–41 330 693 | 21 292 | 15 775–29 911 |
50–64 | 10 484 802 | 7 860 849–14 346 364 | 16 601 | 12 446–22 715 |
≥65 | 5 636 607 | 4 139 528–8 024 420 | 10 750 | 7895–15 305 |
HHS region | ||||
1 (CT, MA, ME, NH, RI, VT) | 1 910 156 | 1 530 556–2 427 485 | 12 860 | 10 304–16 343 |
2 (NJ, NY, PR, VI) | 8 977 706 | 6 780 805–12 534 610 | 31 555 | 23 834–44 057 |
3 (DE, DC, MD, PA, VA, WV) | 3 759 656 | 3 025 633–4 721 730 | 12 190 | 9810–15 309 |
4 (AL, FL, GA, KY, MS, NC, SC, TN) | 12 107 021 | 9 741 202–15 448 374 | 18 234 | 14 671–23 266 |
5 (IL, IN, MI, MN, OH, WI) | 6 324 790 | 5 002 112–8 272 471 | 12 037 | 9520–15 744 |
6 (AR, LA, NM, OK, TX) | 7 315 403 | 5 856 636–9 423 602 | 17 248 | 13 808–22 218 |
7 (IA, KS, MO, NE) | 2 122 340 | 1 684 158–2 788 524 | 15 027 | 11 925–19 744 |
8 (CO, MT, ND, SD, UT, WY) | 1 569 175 | 1 250 443–2 013 970 | 12 927 | 10 301–16 591 |
9 (AZ, CA, HI, NV, AS, MP, FSM, GU, RMI, PW) | 7 243 925 | 5 876 211–9 098 261 | 14 153 | 11 481–17 776 |
10 (AK, ID, OR, WA) | 1 391 488 | 1 106 862–1 775 644 | 9787 | 7785–12 489 |
. | Estimated Total Infections . | 95% UI . | Rate, per 100 000a . | 95% UI . |
---|---|---|---|---|
Overallb | 52 885 526 | 42 527 569–66 810 205 | 16 165 | 12 999–20 421 |
Age group (years) | ||||
0–4 | 1 342 212 | 1 022 465–1 811 583 | 6775 | 5161–9145 |
5–17 | 5 538 766 | 4 222 053–7 451 900 | 10 336 | 7879–13 906 |
18–49 | 29 421 481 | 21 798 393–41 330 693 | 21 292 | 15 775–29 911 |
50–64 | 10 484 802 | 7 860 849–14 346 364 | 16 601 | 12 446–22 715 |
≥65 | 5 636 607 | 4 139 528–8 024 420 | 10 750 | 7895–15 305 |
HHS region | ||||
1 (CT, MA, ME, NH, RI, VT) | 1 910 156 | 1 530 556–2 427 485 | 12 860 | 10 304–16 343 |
2 (NJ, NY, PR, VI) | 8 977 706 | 6 780 805–12 534 610 | 31 555 | 23 834–44 057 |
3 (DE, DC, MD, PA, VA, WV) | 3 759 656 | 3 025 633–4 721 730 | 12 190 | 9810–15 309 |
4 (AL, FL, GA, KY, MS, NC, SC, TN) | 12 107 021 | 9 741 202–15 448 374 | 18 234 | 14 671–23 266 |
5 (IL, IN, MI, MN, OH, WI) | 6 324 790 | 5 002 112–8 272 471 | 12 037 | 9520–15 744 |
6 (AR, LA, NM, OK, TX) | 7 315 403 | 5 856 636–9 423 602 | 17 248 | 13 808–22 218 |
7 (IA, KS, MO, NE) | 2 122 340 | 1 684 158–2 788 524 | 15 027 | 11 925–19 744 |
8 (CO, MT, ND, SD, UT, WY) | 1 569 175 | 1 250 443–2 013 970 | 12 927 | 10 301–16 591 |
9 (AZ, CA, HI, NV, AS, MP, FSM, GU, RMI, PW) | 7 243 925 | 5 876 211–9 098 261 | 14 153 | 11 481–17 776 |
10 (AK, ID, OR, WA) | 1 391 488 | 1 106 862–1 775 644 | 9787 | 7785–12 489 |
Abbreviations: AS, American Samoa; CDC, Centers for Disease Control and Prevention; FSM, Federated States of Micronesia; GU, Guam; HHS, Department of Health and Human Services; MP, Northern Mariana Islands; PR, Puerto Rico; PW, Palau; RMI, Marshall Islands; UI, uncertainty interval; VI, US Virgin Islands.
aPopulation estimated using CDC Wonder Bridged-Race estimates [18].
bDue to rounding, age group and region estimates may not sum to overall estimates.
DISCUSSION
We estimated that nearly 53 million SARS-CoV-2 infections, including 45 million symptomatic illnesses and 2.4 million associated hospitalizations, may have occurred in the United States through 30 September 2020, with variation by geographic region, age group, and time. These preliminary estimates demonstrate the large incidence of disease in the US population and better quantify the impact of the COVID-19 pandemic on the healthcare system and society, and will be updated as more data on underdetection become available.
From past experiences with influenza [26], another respiratory virus associated with a large proportion of mild illness and an overlapping clinical syndrome with COVID-19, laboratory-confirmed cases reported through surveillance systems underestimate total infections. We adapted our current approach from methods to estimate the influenza A/H1N1pdm09 prevalence in the United States during the 2009 pandemic [12]. Our preliminary estimates indicate approximately 1 in 8, or 13%, of total SARS-CoV-2 infections were recognized and reported through the end of September. Similarly, a recent serologic survey of SARS-CoV-2 antibodies in 10 geographically diverse US sites from 23 March to 12 May of 2020 estimated that the total number of SARS-CoV-2 infections was at least 10 (range by US site: 6–24) for every reported case [3], with improvements in this ratio by later time points. Severe cases were more likely to be detected and reported; we estimated 2.5 hospitalized patients for each hospitalized case reported. In the Explorys EHR data, the proportion of intensive care unit patients tested for SARS-CoV-2 was more than 90% by the end of September, although testing remained lower among other inpatients with ARI, and even lower for ARI visits in outpatient settings (Supplementary Figure 1, Supplementary Table 6).
For comparison, the COVID-19–associated Hospitalization Surveillance Network (COVID-NET) is an active, population-based surveillance system for laboratory-confirmed SARS-CoV-2–associated hospitalizations in defined areas of 14 states [27]. While direct comparisons with COVID-NET are imperfect due to the narrower geographic area of the surveillance sites, in 10 of the 14 sites our estimated hospitalization rates by region were 1.5–3.5 times higher than the reported rates from individual sites within those regions by the end of September, similar to the range of our estimated underdetection multiplier for confirmed hospitalizations. Likewise, COVID-NET showed similar trends across age; adults aged 65 years and older had 5–6 times higher rates of hospitalizations than younger adults aged 18–49 years [28]. Both also showed lower hospitalization rates among children [29, 30].
For comparison of population-level incidence of infection, the estimated 36 million infections represent approximately 16% of the US population, ranging from 9% to 31% across regions of the country. This is higher than seroprevalence estimates from a nationwide commercial laboratory seroprevalence survey, which found that 1%–22% of various state populations had antibodies to SARS-CoV-2 by early August, although our estimates include 2 more months of circulation [31]. There remain uncertainties in the interpretation of seroprevalence estimates, including how they vary by the population surveyed, the serologic assays used, the proportion of infected cases with a detectable antibody response, and how long antibody detection persists after infection. Additional studies and sources of data on population-based incidence will help resolve these concerns and provide better national estimates of illness and infection.
We recognize that our model has limitations. From almost a decade of monitoring data on testing practices for influenza [32, 33], testing rates and the use of more sensitive molecular testing have varied by jurisdictions, care settings, age, and disease severity [34]. The availability and use of testing for SARS-CoV-2 have changed rapidly over time; thus far, data on the proportion of persons who are tested for COVID-19 and how this varies across all the previously described factors remain limited. Although data on testing by time, healthcare setting, and age were available, they lacked the coverage to allow for geographic-specific model inputs. These data limitations could have resulted in overestimation of cases from areas with higher testing rates, including some hospitals that are performing universal testing or have more outpatient testing facilities and active contact tracing. Likewise, we may have underestimated in areas with lower testing and contact tracing. Additionally, some infections, such as those among healthcare workers or from outbreaks in congregate residential settings, may be more likely to be tested and nationally reported compared with the general population, and could overestimate nonhospitalized cases and infections. We continue to seek information on the proportion of cases and testing rates in various settings to improve estimates. With limited but growing information regarding the spectrum of clinical manifestations from SARS-CoV-2 infection, there could be a lower index of suspicion of COVID-19 for patients who present with nonspecific and nonrespiratory symptoms; these cases may be less likely to be detected and reported. All of this highlights the importance of having data to monitor the proportions of patients with different clinical syndromes who are being tested for SARS-CoV-2 infection in a variety of healthcare and geographic settings, and not just total numbers of tests performed. Finally, in some heavily affected areas, the size of the outbreaks exceeded capacities to complete detailed case reporting, including patient age and hospitalization status. For cases with missing hospitalization status, we imputed the proportion of reported cases who were hospitalized from the subset with complete data, but it is unclear if age and hospitalization status were missing at random [35]. If not random, and the data were more complete for hospitalized patients, the true hospitalization rate would be lower than we imputed, and the number of hospitalized cases would be lower than we estimated. Furthermore, this was hospitalization status at the time of the case report and would miss those diagnosed as an outpatient but who became hospitalized after they were reported as a case; thus, our estimates of hospitalization may be an underestimate.
Despite these limitations, our model provides a relatively simple approach to illustrate why there are more persons who have had a SARS-CoV-2 infection than the reported confirmed case counts at multiple levels of disease severity. We used data currently available to provide a preliminary estimate of the overall incidence of SARS-CoV-2 infection, illness, and hospitalization in the United States. The CDC is actively working on refining methods to synthesize information across multiple data sources to better describe the national burden of SARS-CoV-2 infection on an ongoing basis and will update estimates as data become available.
In summary, we estimated that in the United States through 30 September 2020 there were approximately 53 million total SARS-CoV-2 infections, including 45 million symptomatic illnesses and 2.4 million hospitalizations, with large variations by age group and geographic area. This indicates that approximately 84% of the US population has not yet been infected and thus most of the country remains at risk, despite already high rates of hospitalization. Improved estimates of SARS-CoV-2 infections, symptomatic illnesses, and hospitalizations over time are critical to our understanding of the severity and burden of this new virus.
Supplementary Data
Supplementary materials are available at Clinical Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.
Notes
Acknowledgments. The authors acknowledge the following additional individuals for their contribution to this manuscript. They thank Ryan Threlkel and Catherine Bozio at the Centers for Disease Control and Prevention for assistance on various parts of the analysis. They appreciate the efforts of John Brownstein, Jared Hawkins, Benjamin Rader, Kara Sewalk, Autumn Gertz, Christopher Remmel, Christina Astley, Thomas McMennamin, and Lakshmi Yajurvedi from Boston Children’s Hospital for their work with COVID Near You and Flu Near You. They thank Teresa Gibson, Bill Saunders, Brian Goodness, Kay Miller, Sarah Bloemers, Tim Burrell, and Shannon Harrer from IBM Watson for their assistance with the Explorys Health Record Database.
Disclaimer. The findings and conclusions in this report are those of the author(s) and do not necessarily represent the official position of the Centers for Disease Control and Prevention.
Potential conflicts of interest. The authors: No reported conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.
References
COVID Near You.
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